The AI Revolution and the Bittensor Network: A New Paradigm for Reshaping Collective Intelligence

The Historical Background of the AI Revolution

In recent years, artificial intelligence technology has made rapid advances, achieving significant breakthroughs in areas such as deep learning and natural language processing, with AI applications penetrating various industries. The emergence of ChatGPT in 2022 ignited the entire AI industry, followed by a wave of various AI generation tools and "AI+" applications. The AI market scale has also shown explosive growth, and it is expected to reach $185 billion by 2030.

However, the current development of the AI industry also faces some challenges. Technology and resources are mainly concentrated in the hands of a few giant companies, leading to issues such as data monopolies and unequal distribution of computing resources. Against this backdrop, the decentralized concept of Web3 provides new possibilities for addressing these issues.

A batch of AI projects combining Web3 concepts have emerged. For example, Fetch.ai builds a decentralized AI economy through blockchain, Numerai uses blockchain and a community of data scientists to predict markets, and Velas creates a high-performance AI + blockchain platform. However, most of these projects are limited to a single application direction.

Bittensor seized this opportunity by building an AI algorithm platform with a built-in filtering mechanism through blockchain competition and incentive mechanisms, providing a fertile ground for high-quality AI projects. This innovative model is expected to reshape the current development landscape of the AI industry.

Bittensor Project Overview

Bittensor is a decentralized machine learning network and digital goods marketplace. It has the following characteristics:

1. Decentralized architecture: Operates on a distributed node network, avoiding data centralization issues.

2. Fair incentive mechanism: rewards distributed based on contribution, encouraging active participation from all parties.

3. Open machine learning resources: Providing services for individuals and organizations in need of AI computing power.

4. Diversified digital commodity trading: not limited to AI models, various types of data can be traded.

Bittensor was initiated by a group of technology enthusiasts in 2021, built on the Substrate framework. The project's development history is as follows:

• 2022: Released Alpha version, validating the feasibility of decentralized AI. Introduced Yuma consensus mechanism.
• 2023: Release of the Beta version and introduction of the TAO token incentive model.
• 2024: Integrate DHT technology to enhance data storage efficiency, expand subnet and digital goods market.

The native token TAO of Bittensor has a total supply of 21 million coins, halving every 4 years. TAO is distributed through fair issuance, with no pre-mining or team allocation. Currently, a block is generated every 12 seconds, and each block rewards 1 TAO.

As of now, the Bittensor network has over 100,000 accounts, of which 80% are active accounts. The price of TAO tokens has increased by several times in the past year, with a current market value of approximately 2.278 billion USD.

Bittensor's Subnet Architecture

The Bittensor network consists of multiple subnets, each with unique functions and incentive mechanisms. Subnets are the most important architectural units of Bittensor and include the following roles:

• Subnet Owner: Provide the underlying code and design incentive mechanisms
• Miners: Run services and compete for rewards
• Validator: Evaluate miner performance and earn staking rewards

The TAO reward distribution for the subnet is usually: 18% to the owners, 41% to the validators, and 41% to the miners. Each subnet has 256 slots, with 64 allocated to validators and 192 allocated to miners.

Subnets need to register to join the network, with an initial registration fee of 100 TAO. After registration, there is a 7-day immunity period. When all subnet slots are full, the subnet with the lowest emissions that is not in the immunity period will be replaced by a new subnet. Therefore, subnets need to continuously increase the staking amount of validators and the efficiency of miners to ensure survival.

Currently, the Bittensor network has 45 subnets, and it is expected to increase to 64 in the coming months. Some high-quality subnet projects, such as Masa, have received significant funding, demonstrating the development potential of this architecture.

Bittensor's Consensus and Proof Mechanism

Bittensor adopts a variety of innovative consensus and proof mechanisms:

1. Proof of Intelligence ( PoI ): Miners prove their contribution by completing intelligent computing tasks.

2. Yuma Consensus: Validators score based on the quality of task completion and derive the final score through an algorithm.

3. Principle of Data Unknowability: Protect data privacy and security.

4. Performance-based reward distribution: Encouraging efficient and high-quality computation and data processing.

5. MOE mechanism: Integrates multiple expert models to work collaboratively and scores and rewards them based on performance.

These mechanisms collectively ensure the decentralization, security, and computational efficiency of the network.

Overview of Bittensor Subnet Projects

Currently, Bittensor has 45 registered subnets, among which the most notable are:

• Subnetwork 19 Vision: Focused on decentralized image generation and inference.
• Subnet 18 Cortex.t: Build a cutting-edge AI platform, providing text and image services.
• Subnet 1: The earliest text generation subnet.

From the perspective of model categories, in addition to generative models, there are various types such as data processing and trading AI. Subnet projects have significant profit potential, but they also require high-performance hardware and optimized algorithms to survive in the competition.

Future Outlook

1. The Web3+AI sector is expected to continue attracting market attention.

2. Bittensor's technical architecture and market performance are competitive.

3. The subnet mechanism provides AI teams with a low-threshold path for decentralized transformation.

4. As the number of subnets increases, challenges such as uneven project quality and declining returns may arise.

Overall, Bittensor, as an innovative decentralized AI network, demonstrates the potential to reshape collective intelligence. However, its future development still requires ongoing technological innovation and market validation.